Quantum Sensing of Non-Repeatable Events Enhanced by In-Sensor Quantum Reservoir Computing
Abstract
High-density nitrogen-vacancy (NV) ensembles in diamond enable sensitive magnetometry. Many quantum-sensing protocols rely on reproducible target fields, allowing repeated measurements under different sensing conditions. In dynamical decoupling (DD) magnetometry, sweeping the interval between π pulses across repeated measurements enables estimation of the frequency and amplitude of an unknown alternating field. For non-repeatable events, however, the same field waveform cannot be reproduced for measurements under different settings. Here we propose NV-based in-sensor quantum reservoir computing (NV-QRC) for sensing such events. Field-driven many-body dynamics and simultaneous fluorescence readout from multiple spatial regions provide a classical classifier with multiple features from a single event. For binary phase classification, we benchmark NV-QRC against DD magnetometry using a single pulse sequence fixed in advance. We show that NV-QRC can retain class-dependent information in regimes where the fixed-DD protocol fails to capture it. These results identify non-repeatable-event sensing as a promising application of quantum reservoir computing.
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BibTeX
@misc{sasaki2026quantum,
title = {{Quantum Sensing of Non-Repeatable Events Enhanced by In-Sensor Quantum Reservoir Computing}},
author = {Daiki Sasaki and Hideaki Kawaguchi and Yuichiro Matsuzaki},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.06292},
eprint = {2609.06292},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.06292},
}
RIS
TY - UNPB
TI - Quantum Sensing of Non-Repeatable Events Enhanced by In-Sensor Quantum Reservoir Computing
AU - Daiki Sasaki
AU - Hideaki Kawaguchi
AU - Yuichiro Matsuzaki
PY - 2026
DA - 2026/09/05
PB - arXiv
DO - 10.48550/arxiv.2609.06292
UR - https://arxiv.org/abs/2609.06292
AB - High-density nitrogen-vacancy (NV) ensembles in diamond enable sensitive magnetometry. Many quantum-sensing protocols rely on reproducible target fields, allowing repeated measurements under different sensing conditions. In dynamical decoupling (DD) magnetometry, sweeping the interval between π pulses across repeated measurements enables estimation of the frequency and amplitude of an unknown alternating field. For non-repeatable events, however, the same field waveform cannot be reproduced for measurements under different settings. Here we propose NV-based in-sensor quantum reservoir computing (NV-QRC) for sensing such events. Field-driven many-body dynamics and simultaneous fluorescence readout from multiple spatial regions provide a classical classifier with multiple features from a single event. For binary phase classification, we benchmark NV-QRC against DD magnetometry using a single pulse sequence fixed in advance. We show that NV-QRC can retain class-dependent information in regimes where the fixed-DD protocol fails to capture it. These results identify non-repeatable-event sensing as a promising application of quantum reservoir computing.
ER -